Category: GIS

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Goats gnaw on geographic given

This post was chosen as an Editor's Selection for ResearchBlogging.orgWe’re used to thinking — or at least assuming — in agrobiodiversity conservation that genetic distance is a monotonically increasing function of geographic distance. It is, after all, a reflection of the great Waldo Tobler’s First Law of Geography: “Everything is related to everything else, but near things are more related than distant things.” And yet. Why should that necessarily be so for crops and livestock, so willfully and incessantly moved to and fro by people in all kinds of unpredictable ways?

A paper just out in Molecular Ecology in effect tests the First Law of Geography with goat genetic diversity data, microsatellites in fact. ((BERTHOULY, C., DO NGOC, D., THÉVENON, S., BOUCHEL, D., NHU VAN, T., DANES, C., GROSBOIS, V., HOANG THANH, H., VU CHI, C., & MAILLARD, J. (2009). How does farmer connectivity influence livestock genetic structure? A case-study in a Vietnamese goat population Molecular Ecology DOI: 10.1111/j.1365-294X.2009.04342.x)). Goat populations were sampled in 3-8 villages in each of 2-5 communes in each of 10 districts in the remote, mountainous, ethnically mixed Vietnamese province of Hang Giang, for a total of 492 animals. The genetic relationships among the animals were then analyzed.

To the surprise of the authors, the spatial structure of the overall population was poorly explained by simple geographic distance. The ethnicity of their keepers and the husbandry practices to which they were subjected did a much better job of predicting the genetic distance between goats. The most dissimilar goats were not necessarily the ones which lived furthest apart, but rather the ones which were kept in different ways by people of different ethnic groups.

So, if you wanted to maximise the diversity in a Vietnamese goat conservation programme, or your chances of hybrid vigour, you’d pick animals from different ethnic groups or production systems, and not necessarily from different ends of the country. Which is something that I remember sort of almost subconsciously doing when I was collecting crops, but it is nice to see it validated like this. I can’t remember offhand similar work on crops, but no doubt Jacob will set me straight soon enough. In the meantime, I revel in a rule proven.

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Reporting threats to agrobiodiversity: A modest proposal

Yesterday Hannes, à propos of something else, reminded me of a post I did a few months back about ProMED which asked the question “Why do we still not have an early warning system for genetic erosion?” Today I read about pestMapper — “[an] internet-based software tool for reporting and mapping biological invasions and other geographical and temporal events.” Whose objectives is basically to make a more participatory, Web 2.0-like ProMED. Coincidence? Maybe. Anyway, this is exactly the kind of thing we’ve been thinking here a “global genetic erosion threat reporting and monitoring portal” might look like. Any thoughts? An idea worth pursuing?

pest map

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Nibbles: Chicory symbolism, Watermelon disease, Olive documentation, Camassia quamash, Pig maps

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Nibbles: Pluots, Village chickens, Axolotl, Artisanal fishing, Fruit and climate change, Stamps, Hornless cattle, Artemisin for malaria, Aquatic agroecosystems characterization, Speciation and ploidy

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Snorkel rice

ResearchBlogging.orgYoko Hattori and colleagues report in Nature ((Hattori, Y., Nagai, K., Furukawa, S., Song, X., Kawano, R., Sakakibara, H., Wu, J., Matsumoto, T., Yoshimura, A., Kitano, H., Matsuoka, M., Mori, H., & Ashikari, M. (2009). The ethylene response factors SNORKEL1 and SNORKEL2 allow rice to adapt to deep water Nature, 460 (7258), 1026-1030 DOI: 10.1038/nature08258)) that they have identified two genes involved in the awesome elongation of deep water rice; the type of rice that can grow in several meters deep water. The genes, baptized SNORKEL1 and SNORKEL2, can now be identified with molecular markers and crossed into popular rice varieties. The BBC has a nice video comparing — I assume — genetically otherwise nearly identical rice varieties with and without the genes.

The avid reader will remember the runner-up entry in The Competion about the sub-1 gene ((

Kenong Xu, Xia Xu, Takeshi Fukao, Patrick Canlas, Reycel Maghirang-Rodriguez, Sigrid Heuer, Abdelbagi M. Ismail, Julia Bailey-Serres, Pamela C. Ronald & David J. Mackill, 2006. Sub1A is an ethylene-response-factor-like gene that confers submergence tolerance to rice. Nature 442: 705-708. doi:10.1038/nature04920
)), that is used by IRRI to make rice flood-proof. Some of these new sub-1 varieties, such as Swarna-sub1 are already grown by farmers in India and Bangladesh.

Interestingly, sub-1 does the very opposite of SNORKEL. Sub-1 shuts the plant off to stop elongation, so that it saves its energy, and can recover later. This works great with flash floods if the water recedes after a week or two. But if the water stays for longer than that, the crop dies. With stagnant deep water, a variety with the SNORKEL gene could be a better bet.

If farmers know beforehand that the water is going to be very deep (because it happens most years), they probably already plant deep water varieties (or plant later or do some other smart thing). Deep water rice is somewhat in decline, because of low yield, but it is grown on a very large area, probably about 3.5 million ha worldwide, mostly in India, Bangladesh, Myanmar, Thailand, Indonesia, Vietnam and Cambodia.

However, if flooding is rare it could be more profitable, though risky, to plant other than deep-water varieties. For their earliness, yield, quality, or what not. Adding either the sub-1 or the SNORKEL gene ((The combination of the two would make for an interesting experiment.)) to those varieties would be an insurance policy for flood years. But which gene to choose? And in what variety? And where to grow it? Not an easy question, but we have been trying to answer it.